Systems and methods may be used to prevent attacks on a malware detection system. A method may include modeling a time series of directed graphs using incoming binary files during training of a machine learning system and detecting, during a time-window of the time series, an anomaly based on a directed graph of the time series of directed graphs. The method may include providing an alert that the anomaly has corrupted the machine learning system. The method may include preventing or remedying corruption of the machine learning system.